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Mathias Angermaier

Publications and source records attributed to Mathias Angermaier.

2 recordsLinked to original sources

Characterizing the Dynamics of Conspiracy Related German Telegram Conversations during COVID-19

Conspiracy theories have long drawn public attention, but their explosive growth on platforms like Telegram during the COVID-19 pandemic raises pressing questions about their impact on societal trust, democracy, and public health. We provide a geographical, temporal and network analysis of the structure of of conspiracy-related German-language Telegram chats in a novel large-scale data set. We examine how information flows between regional user groups and influential broadcasting channels, revealing the interplay between decentralized discussions and content spread driven by a small number of key actors. Our findings reveal that conspiracy-related activity spikes during major COVID-19-related events, correlating with societal stressors and mirroring prior research on how crises amplify conspiratorial beliefs. By analysing the interplay between regional, national and transnational chats, we uncover how information flows from larger national or transnational discourse to localised, community-driven discussions. Furthermore, we find that the top 10% of chats account for 94% of all forwarded content, portraying the large influence of a few actors in disseminating information. However, these chats operate independently, with minimal interconnection between each other, primarily forwarding messages to low-traffic groups. Notably, 43% of links shared in the data set point to untrustworthy sources as identified by NewsGuard, a proportion far exceeding their share on other platforms and in other discourse contexts, underscoring the role of conspiracy-related discussions on Telegram as vector for the spread of misinformation.

cs.SI

The Schwurbelarchiv: a German Language Telegram dataset for the Study of Conspiracy Theories

Sociality borne by language, as is the predominant digital trace on text-based social media platforms, harbours the raw material for exploring a multitude of social phenomena. Distinctively, the messaging service Telegram provides functionalities that allow for socially interactive as well as one-to-many communication. Our Telegram dataset contains over 5,800 groups and channels and 63 million messages, originating from a data-hoarding initiative named the ``Schwurbelarchiv'' (from German schwurbeln: speaking nonsense). Uniquely, it includes the transcriptions of over 3 million audio and video files. While the raw data was previously archived on the Internet Archive by an anonymous data hoarder, it was stored in a format that is difficult to process and largely inaccessible for systematic research. Our contribution consists of parsing, cleaning, and validating this raw archive, pseudonymising user data, and transcribing roughly 126,000 hours of audio and video content, thereby transforming this data hoard into a structured, research-ready dataset. This dataset publication details the structure, scope, and methodological specifics of the Schwurbelarchiv, emphasising its relevance for further research on the German-language conspiracy-theory-related discourse. We validate its predominantly German origin by linguistic and temporal markers and situate it within the context of similar datasets. We describe process and extent of the transcription of multimedia files. Thanks to this effort the dataset uniquely supports analysis of text from originally multimodal sources like voice messages and videos to investigate online social dynamics and content dissemination. Researchers can employ this resource to explore societal dynamics related to misinformation, political extremism, opinion adaptation, and social network structures.

cs.SI